Nitrogen sources in the Mississippi River basin have been linked to degradation of stream ecology and to Gulf of Mexico hypoxia. In 2013, the USGS and the USEPA characterized water quality stressors and ecological conditions in 100 wadeable streams across the midwestern United States. Wet conditions in 2013 followed a severe drought in 2012, a weather pattern associated with elevated nitrogen concentrations and loads in streams. Nitrate concentrations during the May to August 2013 sampling period ranged from <0.04 to 41.8 mg L−1 as N (mean, 5.31 mg L−1). Observed mean May to June nitrate concentrations at the 100 sites were compared with May to June concentrations predicted from a regression model developed using historical nitrate data. Observed concentrations for 17 sites, centered on Iowa and southern Minnesota, were outside the 95% confidence interval of the regression-predicted mean, indicating that they were anomalously high. The sites with a nitrate anomaly had significantly higher May to June nitrate concentrations than sites without an anomaly (means, 19.8 and 3.6 mg L−1, respectively) and had higher antecedent precipitation indices, a measure of the departure from normal precipitation, in 2012 and 2013. Correlations between nitrate concentrations and watershed characteristics and nitrogen and oxygen isotopes of nitrate indicated that fertilizer and manure used in crop production, principally corn, were the dominant sources of nitrate. The anomalously high nitrate levels in parts of the Midwest in 2013 coincide with reported higher-than-normal nitrate loads in the Mississippi River.
","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2015.12.0591","usgsCitation":"Van Metre, P., Frey, J.W., Musgrove, M., Nakagaki, N., Qi, S.L., Mahler, B., Wieczorek, M., and Button, D.T., 2016, High nitrate concentrations in some Midwest United States streams in 2013 after the 2012 drought: Journal of Environmental Quality, v. 45, no. 5, p. 1696-1704, https://doi.org/10.2134/jeq2015.12.0591.","productDescription":"9 p.","startPage":"1696","endPage":"1704","ipdsId":"IP-064530","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":470355,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2015.12.0591","text":"Publisher Index Page"},{"id":337440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.36035156249999,\n 36.63316209558658\n ],\n [\n -82.265625,\n 36.63316209558658\n ],\n [\n -82.265625,\n 45.42929873257377\n ],\n [\n -99.36035156249999,\n 45.42929873257377\n ],\n [\n -99.36035156249999,\n 36.63316209558658\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9de4b0849ce9795e82","contributors":{"authors":[{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":172246,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":false,"id":683826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frey, Jeffrey W. 0000-0002-3453-5009 jwfrey@usgs.gov","orcid":"https://orcid.org/0000-0002-3453-5009","contributorId":487,"corporation":false,"usgs":true,"family":"Frey","given":"Jeffrey","email":"jwfrey@usgs.gov","middleInitial":"W.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":683828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nakagaki, Naomi 0000-0003-3653-0540 nakagaki@usgs.gov","orcid":"https://orcid.org/0000-0003-3653-0540","contributorId":1067,"corporation":false,"usgs":true,"family":"Nakagaki","given":"Naomi","email":"nakagaki@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":683831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wieczorek, Michael E. 0000-0003-0999-5457 mewieczo@usgs.gov","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":178736,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael E.","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683833,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Button, Daniel T. 0000-0002-7479-884X dtbutton@usgs.gov","orcid":"https://orcid.org/0000-0002-7479-884X","contributorId":2084,"corporation":false,"usgs":true,"family":"Button","given":"Daniel","email":"dtbutton@usgs.gov","middleInitial":"T.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683832,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70192092,"text":"70192092 - 2016 - Adult nest attendance and diet of nestling Resplendent Quetzals (Pharomachrus mocinno) in the Talamanca Mountains of southern Cosa Rica","interactions":[],"lastModifiedDate":"2017-10-25T15:13:55","indexId":"70192092","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2967,"text":"Ornitologia Neotropical","active":true,"publicationSubtype":{"id":10}},"title":"Adult nest attendance and diet of nestling Resplendent Quetzals (Pharomachrus mocinno) in the Talamanca Mountains of southern Cosa Rica","docAbstract":"Resplendent Quetzals (Pharomachrus mocinno) inhabit mid to high elevation forests from southern Mexico to Panama. Lipid rich fruits from the Lauraceae family have been found to account for a large proportion of adult diet across their annual life cycle. To better understand the relationship between quetzals and Lauraceae during the breeding season, we studied food deliveries to nestlings in the Talamanca Mountains at San Gerardo de Dota, Costa Rica in the Rio Savegre watershed. Our study had four primary objectives: 1) determine parental contribution of males and females feeding nestling quetzals, 2) determine type of food delivered to nestling quetzals, 3) determine if deliveries of fruit items were related to their abundance and/or nutritional content and 4) determine if Lauraceae fruits made up a large proportion of nestling diets based on the high preference quetzals have displayed for fruits from this plant family. Hourly delivery rates were similar for the male and female (1.24 ± 0.68 and 1.44 ± 0.84). During the first 6 days, the largest proportion of the diet was animal prey; primarily lizards and beetles. After day 6, fruit rapidly became the dominant food item delivered to nestlings until fledging. The dominant number of fruits delivered to nestling quetzals were fruits from the Lauraceae family and included Ocotea holdrigeiana, Necatandra cufodontisii, and Aiouea costaricensis. All three had some of the highest protein and lipid content of all fruits delivered to nestlings. O. holdrigeiana had the highest protein and lipid content of all fruits delivered, had the lowest relative abundance, and was delivered more frequently than all other fruits. Conservation strategies for this species should take into account not just increasing available habitat, but also increasing habitat quality by focusing on species composition to provide abundant food plants for the Resplendent Quetzal to forage.
","language":"English","publisher":"Sociedad de Ornitología Neotropical","usgsCitation":"Carleton, S.A., 2016, Adult nest attendance and diet of nestling Resplendent Quetzals (Pharomachrus mocinno) in the Talamanca Mountains of southern Cosa Rica: Ornitologia Neotropical, v. 27, p. 181-188.","productDescription":"8 p.","startPage":"181","endPage":"188","ipdsId":"IP-076978","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":347396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347395,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://journals.sfu.ca/ornneo/index.php/ornneo/article/view/116"}],"country":"Costa Rica","volume":"27","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a7e4b0220bbd9d9f6f","contributors":{"authors":[{"text":"Carleton, Scott A. 0000-0001-9609-650X scarleton@usgs.gov","orcid":"https://orcid.org/0000-0001-9609-650X","contributorId":4060,"corporation":false,"usgs":true,"family":"Carleton","given":"Scott","email":"scarleton@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714180,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70192566,"text":"70192566 - 2016 - Statistically extracted fundamental watershed variables for estimating the loads of total nitrogen in small streams","interactions":[],"lastModifiedDate":"2017-10-26T14:43:51","indexId":"70192566","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1550,"text":"Environmental Modeling & Assessment","onlineIssn":" 1573-296","printIssn":"1420-2026","active":true,"publicationSubtype":{"id":10}},"title":"Statistically extracted fundamental watershed variables for estimating the loads of total nitrogen in small streams","docAbstract":"Accurate estimation of total nitrogen loads is essential for evaluating conditions in the aquatic environment. Extrapolation of estimates beyond measured streams will greatly expand our understanding of total nitrogen loading to streams. Recursive partitioning and random forest regression were used to assess 85 geospatial, environmental, and watershed variables across 636 small (<585 km2) watersheds to determine which variables are fundamentally important to the estimation of annual loads of total nitrogen. Initial analysis led to the splitting of watersheds into three groups based on predominant land use (agricultural, developed, and undeveloped). Nitrogen application, agricultural and developed land area, and impervious or developed land in the 100-m stream buffer were commonly extracted variables by both recursive partitioning and random forest regression. A series of multiple linear regression equations utilizing the extracted variables were created and applied to the watersheds. As few as three variables explained as much as 76 % of the variability in total nitrogen loads for watersheds with predominantly agricultural land use. Catchment-scale national maps were generated to visualize the total nitrogen loads and yields across the USA. The estimates provided by these models can inform water managers and help identify areas where more in-depth monitoring may be beneficial.
","language":"English","publisher":"Springer","doi":"10.1007/s10666-016-9525-3","usgsCitation":"Kronholm, S.C., Capel, P.D., and Terziotti, S., 2016, Statistically extracted fundamental watershed variables for estimating the loads of total nitrogen in small streams: Environmental Modeling & Assessment, v. 21, no. 6, p. 681-690, https://doi.org/10.1007/s10666-016-9525-3.","productDescription":"10 p.","startPage":"681","endPage":"690","ipdsId":"IP-076954","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":438501,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TX3CGB","text":"USGS data release","linkHelpText":"Data on annual total nitrogen loads and watershed characteristics used to develop a method to estimate the total nitrogen loads in small streams"},{"id":347496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-26","publicationStatus":"PW","scienceBaseUri":"5a07e98de4b09af898c8cc26","contributors":{"authors":[{"text":"Kronholm, Scott C.","contributorId":184190,"corporation":false,"usgs":false,"family":"Kronholm","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":716220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":716219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716221,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178070,"text":"fs20163096 - 2016 - Selected streambed sediment compounds and water toxicity results for Westside Creeks, San Antonio, Texas, 2014","interactions":[],"lastModifiedDate":"2016-12-01T13:36:42","indexId":"fs20163096","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3096","title":"Selected streambed sediment compounds and water toxicity results for Westside Creeks, San Antonio, Texas, 2014","docAbstract":"The Alazán, Apache, Martínez, and San Pedro Creeks in San Antonio, Texas, are part of a network of urban tributaries to the San Antonio River, known locally as the Westside Creeks. The Westside Creeks flow through some of the oldest neighborhoods in San Antonio. The disruption of streambed sediment is anticipated during a planned restoration to improve and restore the environmental condition of 14 miles of channelized sections of the Westside Creeks in San Antonio. These construction activities can create the potential to reintroduce chemicals found in the sediments into the ecosystem where, depending on hydrologic and environmental conditions, they could become bioavailable and toxic to aquatic life. Elevated concentrations of sediment-associated contaminants often are measured in urban areas such as San Antonio, Tex. Contaminants found in sediment can affect the health of aquatic organisms that ingest sediment. The gradual accumulation of trace elements and organic compounds in aquatic organisms can cause various physiological issues and can ultimately result in death of the aquatic organisms; in addition, subsequent ingestion of aquatic organisms can transfer the accumulated contaminants upward through the food chain (a process called biomagnification).
The U.S. Geological Survey, in cooperation with the San Antonio River Authority, collected sediment samples and water samples for toxicity testing from sites on the Westside Creeks as part of an initial characterization of selected contaminants in the study area. Samples were collected in January 2014 during base-flow conditions and again in May 2104 after a period of stormwater runoff (poststorm conditions). Sediment samples were analyzed for selected constituents, including trace elements and organic contaminants such as pesticides, brominated flame retardants, polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs). In addition, as an indicator of ecological health (and possibly bioavailability of contaminants in disturbed streambed sediments), the toxicity of water samples to the indicator species Pimephales promelas (fathead minnow) was evaluated by using standard 7-day water-toxicity testing.
","language":"English, Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163096","collaboration":"Prepared in cooperation with the San Antonio River Authority","usgsCitation":"Crow, C.L., Wilson, J.T., and Kunz, J.L., 2016, Selected streambed sediment compounds and water toxicity results for Westside Creeks, San Antonio, Texas, 2014: U.S. Geological Survey Fact Sheet 2016–3096, 4 p., https://doi.org/10.3133/fs20163096.","productDescription":"Document: 4 p.; Companion File","startPage":"1","endPage":"4","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-079315","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":331371,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3096/fs20163096_SpanishVersion.pdf","text":"Spanish Fact Sheet","size":"613 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3096 Spanish Version"},{"id":331374,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2016/5136/sir20165136.pdf","text":"SIR 2016–5136","size":"8.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5136"},{"id":331370,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3096/fs20163096.pdf","text":"English Fact Sheet","size":"667 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3096 English Version"},{"id":331369,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3096/coverthb.jpg"}],"country":"United States","state":"Texas","city":"San Antonio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.604167,\n 29.475\n ],\n [\n -98.604167,\n 29.3625\n ],\n [\n -98.454167,\n 29.3625\n ],\n [\n -98.454167,\n 29.475\n ],\n [\n -98.604167,\n 29.475\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
For animals that forage widely, protecting young from predation can span relatively long time periods due to the inability of young to travel with and be protected by their parents. Moving relatively immobile young to improve access to important resources, limit detection of concentrated scent by predators, and decrease infestations by ectoparasites can be advantageous. Moving young, however, can also expose them to increased mortality risks (e.g., accidents, getting lost, predation). For group-living animals that live in variable environments and care for young over extended time periods, the influence of biotic factors (e.g., group size, predation risk) and abiotic factors (e.g., temperature and precipitation) on the decision to move young is unknown. We used data from 25 satellite-collared wolves ( Canis lupus ) in Idaho, Montana, and Yellowstone National Park to evaluate how these factors could influence the decision to move pups during the pup-rearing season. We hypothesized that litter size, the number of adults in a group, and perceived predation risk would positively affect the number of times gray wolves moved pups. We further hypothesized that wolves would move their pups more often when it was hot and dry to ensure sufficient access to water. Contrary to our hypothesis, monthly temperature above the 30-year average was negatively related to the number of times wolves moved their pups. Monthly precipitation above the 30-year average, however, was positively related to the amount of time wolves spent at pup-rearing sites after leaving the natal den. We found little relationship between risk of predation (by grizzly bears, humans, or conspecifics) or group and litter sizes and number of times wolves moved their pups. Our findings suggest that abiotic factors most strongly influence the decision of wolves to move pups, although responses to unpredictable biotic events (e.g., a predator encountering pups) cannot be ruled out.
","language":"English","publisher":"American Society of Mammalogists","doi":"10.1093/jmammal/gyw114","usgsCitation":"Ausband, D., Mitchell, M.S., Bassing, S.B., Nordhagen, M., Smith, D., and Stahler, D.R., 2016, Dog days of summer: Influences on decision of wolves to move pups: Journal of Mammalogy, v. 97, no. 5, p. 1282-1287, https://doi.org/10.1093/jmammal/gyw114.","productDescription":"6 p.","startPage":"1282","endPage":"1287","ipdsId":"IP-076548","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470363,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyw114","text":"Publisher Index Page"},{"id":337431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"58c7af9de4b0849ce9795e80","contributors":{"authors":[{"text":"Ausband, David E.","contributorId":51441,"corporation":false,"usgs":true,"family":"Ausband","given":"David E.","affiliations":[],"preferred":false,"id":683907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":683854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bassing, Sarah B.","contributorId":81006,"corporation":false,"usgs":true,"family":"Bassing","given":"Sarah","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":683908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nordhagen, Matthew","contributorId":189127,"corporation":false,"usgs":false,"family":"Nordhagen","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":683909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Douglas W.","contributorId":179181,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas W.","affiliations":[],"preferred":false,"id":683910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stahler, Daniel R.","contributorId":179180,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":683911,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193338,"text":"70193338 - 2016 - Response of fish assemblages to decreasing acid deposition in Adirondack Mountain lakes","interactions":[],"lastModifiedDate":"2018-02-14T11:45:45","indexId":"70193338","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5590,"text":"NYSERDA Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"17-01","title":"Response of fish assemblages to decreasing acid deposition in Adirondack Mountain lakes","docAbstract":"The CAA and other federal regulations have clearly reduced emissions of NOx and SOx, acidic deposition, and the acidity and toxicity of waters in the ALTM lakes, but these changes have not triggered widespread recovery of brook trout populations or fish communities. The lack of detectable biological recovery appears to result from relatively recent chemical recovery and an insufficient period for species populations to take advantage of improved water quality. Recovery of extirpated species’ populations may simply require more time for individuals to migrate to and repopulate formerly occupied lakes. Supplemental stocking of selected species may be required in some lakes with no remnant (or nearby) populations or with physical barriers between the recovered lake and source populations. The lack of detectable biological recovery could also be related to our inability to calculate measures of uncertainty or error and, thus, examine temporal changes or differences in populations and community metrics in more depth (e.g., within individual lakes) using existing datasets. Indeed, recovery of brook trout populations and partial recovery of fish communities are documented in several lakes of the region, both with and without human intervention. Multiple fish surveys (annually or within the same year) or the use of mark and recapture methods within individual lakes would help alleviate the issue (provide measures of error for key fishery metrics) within the context of a more focused sampling strategy. Efforts to evaluate and detect recovery in fish assemblages from streams may be more effective than in lakes because various life stages, species’ populations, and entire assemblages are easier to quantify, with known levels of error, in streams than in lakes. Such long-term monitoring efforts could increase our ability to detect and quantify biological recovery in recovering (neutralizing) surface waters throughout the Adirondack Region.","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Baldigo, B.P., Roy, K., and Driscoll, C.T., 2016, Response of fish assemblages to decreasing acid deposition in Adirondack Mountain lakes: NYSERDA Report 17-01, iv, 15 p.","productDescription":"iv, 15 p.","numberOfPages":"24","ipdsId":"IP-084560","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":351604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347915,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/-/media/Files/Publications/Research/Environmental/17-01-Response-fish-Assemblages-decreasing-acid-deposition.pdf"}],"country":"United States","state":"New York","otherGeospatial":"Adirondacks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.25,\n 43\n ],\n [\n -73.311767578125,\n 43\n ],\n [\n -73.311767578125,\n 44.88798544802555\n ],\n [\n -75.25,\n 44.88798544802555\n ],\n [\n -75.25,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee92ee4b0da30c1bfc532","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Karen","contributorId":178106,"corporation":false,"usgs":false,"family":"Roy","given":"Karen","affiliations":[],"preferred":false,"id":718737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":718738,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186922,"text":"70186922 - 2016 - Spatial and ecological variation in dryland ecohydrological responses to climate change: implications for management","interactions":[],"lastModifiedDate":"2017-04-14T13:06:19","indexId":"70186922","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and ecological variation in dryland ecohydrological responses to climate change: implications for management","docAbstract":"Ecohydrological responses to climate change will exhibit spatial variability and understanding the spatial pattern of ecological impacts is critical from a land management perspective. To quantify climate change impacts on spatial patterns of ecohydrology across shrub steppe ecosystems in North America, we asked the following question: How will climate change impacts on ecohydrology differ in magnitude and variability across climatic gradients, among three big sagebrush ecosystems (SB-Shrubland, SB-Steppe, SB-Montane), and among Sage-grouse Management Zones? We explored these potential changes for mid-century for RCP8.5 using a process-based water balance model (SOILWAT) for 898 big sagebrush sites using site- and scenario-specific inputs. We summarize changes in available soil water (ASW) and dry days, as these ecohydrological variables may be helpful in guiding land management decisions about where to geographically concentrate climate change mitigation and adaptation resources. Our results suggest that during spring, soils will be wetter in the future across the western United States, while soils will be drier in the summer. The magnitude of those predictions differed depending on geographic position and the ecosystem in question: Larger increases in mean daily spring ASW were expected for high-elevation SB-Montane sites and the eastern and central portions of our study area. The largest decreases in mean daily summer ASW were projected for warm, dry, mid-elevation SB-Montane sites in the central and west-central portions of our study area (decreases of up to 50%). Consistent with declining summer ASW, the number of dry days was projected to increase rangewide, but particularly for SB-Montane and SB-Steppe sites in the eastern and northern regions. Collectively, these results suggest that most sites will be drier in the future during the summer, but changes were especially large for mid- to high-elevation sites in the northern half of our study area. Drier summer conditions in high-elevation, SB-Montane sites may result in increased habitat suitability for big sagebrush, while those same changes will likely reduce habitat suitability for drier ecosystems. Our work has important implications for where land managers should prioritize resources for the conservation of North American shrub steppe plant communities and the species that depend on them.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1590","usgsCitation":"Palmquist, K.A., Schlaepfer, D., Bradford, J.B., and Lauenroth, W.K., 2016, Spatial and ecological variation in dryland ecohydrological responses to climate change: implications for management: Ecosphere, v. 7, no. 11, e01590; 20 p., https://doi.org/10.1002/ecs2.1590.","productDescription":"e01590; 20 p.","ipdsId":"IP-074039","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1590","text":"Publisher Index Page"},{"id":339736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"58f1e0c9e4b08144348b7df4","contributors":{"authors":[{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":691010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":691012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":691009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":691011,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187376,"text":"70187376 - 2016 - Deglacial temperature history of West Antarctica","interactions":[],"lastModifiedDate":"2018-03-23T13:39:40","indexId":"70187376","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Deglacial temperature history of West Antarctica","docAbstract":"The most recent glacial to interglacial transition constitutes a remarkable natural experiment for learning how Earth’s climate responds to various forcings, including a rise in atmospheric CO2. This transition has left a direct thermal remnant in the polar ice sheets, where the exceptional purity and continual accumulation of ice permit analyses not possible in other settings. For Antarctica, the deglacial warming has previously been constrained only by the water isotopic composition in ice cores, without an absolute thermometric assessment of the isotopes’ sensitivity to temperature. To overcome this limitation, we measured temperatures in a deep borehole and analyzed them together with ice-core data to reconstruct the surface temperature history of West Antarctica. The deglacial warming was
Coastal ecosystems are under increasing pressure from human activity, introduced species, sea level rise, and storm activity. Hurricanes are a powerful destructive force, but can also renew coastal habitats. In 2003, Hurricane Isabel altered the barrier islands of North Carolina, flattening dunes and creating sand flats. American Oystercatchers (Haematopus palliatus) are large shorebirds that inhabit the coastal zone throughout the year. Alternative survival models were evaluated for 699 American Oystercatcher nests on North Core Banks and South Core Banks, North Carolina, USA, from 1999–2007. Nest survival on North Core Banks increased from 0.170 (SE = 0.002) to 0.772 (SE = 0.090) after the hurricane, with a carry-over effect lasting 2 years. A simple year effects model described nest survival on South Core Banks. Habitat had no effect on survival except when the overall rate of nest survival was at intermediate levels (0.300–0.600), when nests on open flats survived at a higher rate (0.600; SE = 0.112) than nests in dune habitat (0.243; SE = 0.094). Predator activity declined on North Core Banks after the hurricane and corresponded with an increase in nest survival. Periodic years with elevated nest survival may offset low annual productivity and contribute to the stability of American Oystercatcher populations.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.039.0402","usgsCitation":"Simons, T.R., and Schulte, S., 2016, Hurricane disturbance benefits nesting American Oystercatchers (Haematopus palliatus): Waterbirds, v. 39, no. 4, p. 327-337, https://doi.org/10.1675/063.039.0402.","productDescription":"11 p.","startPage":"327","endPage":"337","ipdsId":"IP-057574","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":338548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58dcc7d5e4b02ff32c685673","contributors":{"authors":[{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":686695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schulte, Shiloh A.","contributorId":39911,"corporation":false,"usgs":true,"family":"Schulte","given":"Shiloh A.","affiliations":[],"preferred":false,"id":686762,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189314,"text":"70189314 - 2016 - Occurrence of triclocarban and triclosan in an agro-ecosystem following application of biosolids","interactions":[],"lastModifiedDate":"2018-08-08T10:15:31","indexId":"70189314","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence of triclocarban and triclosan in an agro-ecosystem following application of biosolids","docAbstract":"Triclocarban (TCC) and triclosan (TCS), two of the most commonly used antimicrobial compounds, can be introduced into ecosystems by applying wastewater treatment plant biosolids to agricultural fields. Concentrations of TCC and TCS were measured in different trophic levels within a terrestrial food web encompassing land-applied biosolids, soil, earthworms (Lumbricus), deer mice (Peromyscus maniculatus), and eggs of European starlings (Sturnus vulgaris) and American kestrels (Falco sparverius) at an experimental site amended with biosolids for the previous 7 years. The samples from this site were compared to the same types of samples from a reference (biosolids-free) agricultural site. Inter-site comparisons showed that concentrations of both antimicrobials were higher on the experimental site in the soil, earthworms, mice (livers), and European starling eggs, but not American kestrel eggs, compared to the control site. Inter-species comparisons on the experimental site indicated significantly higher TCC concentrations in mice (TCC: 12.6–33.3 ng/g) and in starling eggs (TCC: 15.4–31.4 ng/g) than in kestrel eggs (TCC: 3.6 ng/g). Nesting success of kestrels only was significantly lower on the experimental site compared to the reference site due to nest abandonment. This study demonstrates that biosolids-derived TCC and TCS are present throughout the terrestrial food web, including secondary (e.g., starlings) and tertiary (i.e., kestrels) consumers, after repeated, long-term biosolids application.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.6b01834","usgsCitation":"Sherburne, J.J., Anaya, A.M., Fernie, K.J., Forbey, J.S., Furlong, E.T., Kolpin, D.W., Dufty, A.M., and Kinney, C.A., 2016, Occurrence of triclocarban and triclosan in an agro-ecosystem following application of biosolids: Environmental Science & Technology, v. 50, no. 24, p. 13206-13214, https://doi.org/10.1021/acs.est.6b01834.","productDescription":"9 p.","startPage":"13206","endPage":"13214","ipdsId":"IP-077351","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":343553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"24","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-05","publicationStatus":"PW","scienceBaseUri":"5965b26ce4b0d1f9f05b37f3","contributors":{"authors":[{"text":"Sherburne, Jessica J.","contributorId":194440,"corporation":false,"usgs":false,"family":"Sherburne","given":"Jessica","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":704136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anaya, Amanda M.","contributorId":194441,"corporation":false,"usgs":false,"family":"Anaya","given":"Amanda","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":704137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fernie, Kimberly J.","contributorId":176208,"corporation":false,"usgs":false,"family":"Fernie","given":"Kimberly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":704138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forbey, Jennifer S.","contributorId":194442,"corporation":false,"usgs":false,"family":"Forbey","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":704139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":704140,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704116,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dufty, Alfred M.","contributorId":194443,"corporation":false,"usgs":false,"family":"Dufty","given":"Alfred","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":704141,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kinney, Chad A.","contributorId":56952,"corporation":false,"usgs":true,"family":"Kinney","given":"Chad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704142,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189338,"text":"70189338 - 2016 - The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: An extension of the Plankton Ecology Group (PEG) model","interactions":[],"lastModifiedDate":"2018-10-20T12:29:35","indexId":"70189338","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: An extension of the Plankton Ecology Group (PEG) model","docAbstract":"The use of high-frequency sensors on profiling buoys to investigate physical, chemical, and biological processes in lakes is increasing rapidly. Profiling buoys with automated winches and sensors that collect high-frequency chlorophyll fluorescence (ChlF) profiles in 11 lakes in the Global Lake Ecological Observatory Network (GLEON) allowed the study of the vertical and temporal distribution of ChlF, including the formation of subsurface chlorophyll maxima (SSCM). The effectiveness of 3 methods for sampling phytoplankton distributions in lakes, including (1) manual profiles, (2) single-depth buoys, and (3) profiling buoys were assessed. High-frequency ChlF surface data and profiles were compared to predictions from the Plankton Ecology Group (PEG) model. The depth-integrated ChlF dynamics measured by the profiling buoy data revealed a greater complexity that neither conventional sampling nor the generalized PEG model captured. Conventional sampling techniques would have missed SSCM in 7 of 11 study lakes. Although surface-only ChlF data underestimated average water column ChlF, at times by nearly 2-fold in 4 of the lakes, overall there was a remarkable similarity between surface and mean water column data. Contrary to the PEG model’s proposed negligible role for physical control of phytoplankton during the growing season, thermal structure and light availability were closely associated with ChlF seasonal depth distribution. Thus, an extension of the PEG model is proposed, with a new conceptual framework that explicitly includes physical metrics to better predict SSCM formation in lakes and highlight when profiling buoys are especially informative.
","language":"English","publisher":"International Society of Limnology","doi":"10.5268/IW-6.4.890","usgsCitation":"Brentrup, J.A., Williamson, C.E., Colom-Montero, W., Eckert, W., de Eyto, E., Grossart, H., Huot, Y., Isles, P., Knoll, L.B., Leach, T.H., McBride, C.G., Pierson, D., Pomati, F., Read, J.S., Rose, K.C., Samal, N.R., Staehr, P.A., and Winslow, L.A., 2016, The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: An extension of the Plankton Ecology Group (PEG) model: Inland Waters, v. 6, no. 4, p. 565-580, https://doi.org/10.5268/IW-6.4.890.","productDescription":"16 p.","startPage":"565","endPage":"580","ipdsId":"IP-065599","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":343581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-06-07","publicationStatus":"PW","scienceBaseUri":"5965b26be4b0d1f9f05b37ef","contributors":{"authors":[{"text":"Brentrup, Jennifer A.","contributorId":194457,"corporation":false,"usgs":false,"family":"Brentrup","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williamson, Craig E.","contributorId":146436,"corporation":false,"usgs":false,"family":"Williamson","given":"Craig","email":"","middleInitial":"E.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":704232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colom-Montero, William","contributorId":194458,"corporation":false,"usgs":false,"family":"Colom-Montero","given":"William","email":"","affiliations":[],"preferred":false,"id":704233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eckert, Werner","contributorId":194459,"corporation":false,"usgs":false,"family":"Eckert","given":"Werner","email":"","affiliations":[],"preferred":false,"id":704234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Eyto, Elvira","contributorId":166838,"corporation":false,"usgs":false,"family":"de Eyto","given":"Elvira","email":"","affiliations":[{"id":24549,"text":"Fisheries Ecosystems Advisory Services, Marine Institute, Furnace, Newport, Co. Mayo, Ireland.","active":true,"usgs":false}],"preferred":false,"id":704235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grossart, Hans-Peter 0000-0002-9141-0325","orcid":"https://orcid.org/0000-0002-9141-0325","contributorId":194460,"corporation":false,"usgs":false,"family":"Grossart","given":"Hans-Peter","email":"","affiliations":[],"preferred":false,"id":704236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huot, Yannick","contributorId":194461,"corporation":false,"usgs":false,"family":"Huot","given":"Yannick","email":"","affiliations":[],"preferred":false,"id":704237,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Isles, Peter D. F.","contributorId":194462,"corporation":false,"usgs":false,"family":"Isles","given":"Peter D. F.","affiliations":[],"preferred":false,"id":704238,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Knoll, Lesley B. 0000-0003-0347-5979","orcid":"https://orcid.org/0000-0003-0347-5979","contributorId":194463,"corporation":false,"usgs":false,"family":"Knoll","given":"Lesley","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":704239,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Leach, Taylor H.","contributorId":194464,"corporation":false,"usgs":false,"family":"Leach","given":"Taylor","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":704240,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McBride, Christopher G.","contributorId":130977,"corporation":false,"usgs":false,"family":"McBride","given":"Christopher","email":"","middleInitial":"G.","affiliations":[{"id":7184,"text":"Environmental Research Institute, University of Waikato, Hamilton, New Zealand","active":true,"usgs":false}],"preferred":false,"id":704241,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pierson, Don","contributorId":194465,"corporation":false,"usgs":false,"family":"Pierson","given":"Don","email":"","affiliations":[],"preferred":false,"id":704242,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pomati, Francesco","contributorId":194466,"corporation":false,"usgs":false,"family":"Pomati","given":"Francesco","email":"","affiliations":[],"preferred":false,"id":704243,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704244,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rose, Kevin C.","contributorId":174809,"corporation":false,"usgs":false,"family":"Rose","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":704245,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Samal, Nihar R.","contributorId":150303,"corporation":false,"usgs":false,"family":"Samal","given":"Nihar","email":"","middleInitial":"R.","affiliations":[{"id":17977,"text":"Institute for Sustainable Cities, City University of New York, New York, USA","active":true,"usgs":false}],"preferred":false,"id":704246,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Staehr, Peter A.","contributorId":194467,"corporation":false,"usgs":false,"family":"Staehr","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704247,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":704248,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70175402,"text":"70175402 - 2016 - Trading shallow safety for deep sleep: Juvenile green turtles select deeper resting sites as they grow","interactions":[],"lastModifiedDate":"2018-03-27T09:55:26","indexId":"70175402","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Trading shallow safety for deep sleep: Juvenile green turtles select deeper resting sites as they grow","docAbstract":"To better protect endangered green sea turtles Chelonia mydas, a more thorough understanding of the behaviors of each life stage is needed. Although dive profile analyses obtained using time-depth loggers have provided some insights into habitat use, recent work has shown that more fine-scale monitoring of body movements is needed to elucidate physical activity patterns. We monitored 11 juvenile green sea turtles with tri-axial acceleration data loggers in their foraging grounds in Dry Tortugas National Park, Florida, USA, for periods ranging from 43 to 118 h (mean ± SD: 72.8 ± 27.3 h). Approximately half of the individuals (n = 5) remained in shallow (overall mean depth less than 2 m) water throughout the experiment, whereas the remaining individuals (n = 6) made excursions to deeper (4 to 27 m) waters, often at night. Despite these differences in depth use, acceleration data revealed a consistent pattern of diurnal activity and nocturnal resting in most individuals. Nocturnal depth differences thus do not appear to represent differences in behavior, but rather different strategies to achieve the same behavior: rest. We calculated overall dynamic body acceleration (ODBA) to assess the relative energetic cost of each behavioral strategy in an attempt to explain the differences between them. Animals in deeper water experienced longer resting dives, more time resting per hour, and lower mean hourly ODBA. These results suggest that resting in deeper water provides energetic benefits that outweigh the costs of transiting to deep water and a potential increased risk of predation.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00750","usgsCitation":"Hart, K.M., White, C.F., Iverson, A., and Whitney, N., 2016, Trading shallow safety for deep sleep: Juvenile green turtles select deeper resting sites as they grow: Endangered Species Research, v. 31, p. 61-73, https://doi.org/10.3354/esr00750.","productDescription":"13 p.","startPage":"61","endPage":"73","ipdsId":"IP-072587","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470364,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00750","text":"Publisher Index Page"},{"id":337665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.11363220214844,\n 24.472150437226865\n ],\n [\n -82.6776123046875,\n 24.472150437226865\n ],\n [\n -82.6776123046875,\n 24.795461666933413\n ],\n [\n -83.11363220214844,\n 24.795461666933413\n ],\n [\n -83.11363220214844,\n 24.472150437226865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52cde4b0849ce97c86a4","contributors":{"authors":[{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":645072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Connor F.","contributorId":173554,"corporation":false,"usgs":false,"family":"White","given":"Connor","email":"","middleInitial":"F.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":645073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iverson, Autumn R. 0000-0002-8353-6745","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":173555,"corporation":false,"usgs":false,"family":"Iverson","given":"Autumn R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":645074,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitney, Nick","contributorId":173556,"corporation":false,"usgs":false,"family":"Whitney","given":"Nick","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":645075,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189339,"text":"70189339 - 2016 - Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes","interactions":[],"lastModifiedDate":"2018-07-07T18:28:49","indexId":"70189339","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes","docAbstract":"Ecosystem metabolism and the contribution of carbon dioxide from lakes to the atmosphere can be estimated from free-water gas measurements through the use of mass balance models, which rely on a gas transfer coefficient (k) to model gas exchange with the atmosphere. Theoretical and empirically based models of krange in complexity from wind-driven power functions to complex surface renewal models; however, model choice is rarely considered in most studies of lake metabolism. This study used high-frequency data from 15 lakes provided by the Global Lake Ecological Observatory Network (GLEON) to study how model choice of kinfluenced estimates of lake metabolism and gas exchange with the atmosphere. We tested 6 models of k on lakes chosen to span broad gradients in surface area and trophic states; a metabolism model was then fit to all 6 outputs of k data. We found that hourly values for k were substantially different between models and, at an annual scale, resulted in significantly different estimates of lake metabolism and gas exchange with the atmosphere.
","language":"English","publisher":"International Society of Limnology","doi":"10.1080/IW-6.4.836","usgsCitation":"Dugan, H., Woolway, R., Santoso, A., Corman, J., Jaimes, A., Nodine, E., Patil, V.P., Zwart, J., Brentrup, J.A., Hetherington, A., Oliver, S., Read, J.S., Winter, K., Hanson, P., Read, E., Winslow, L., and Weathers, K., 2016, Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes: Inland Waters, v. 6, no. 4, p. 581-592, https://doi.org/10.1080/IW-6.4.836.","productDescription":"12 p.","startPage":"581","endPage":"592","ipdsId":"IP-056410","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":470372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/iw-6.4.836","text":"Publisher Index Page"},{"id":343583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5965b26be4b0d1f9f05b37ed","contributors":{"authors":[{"text":"Dugan, Hilary A.","contributorId":150191,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","middleInitial":"A.","affiliations":[{"id":17938,"text":"Center for Limnology University of Wisconsin, Madison, WI 53706, US","active":true,"usgs":false}],"preferred":false,"id":704249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woolway, R. Iestyn","contributorId":150345,"corporation":false,"usgs":false,"family":"Woolway","given":"R. Iestyn","affiliations":[{"id":18007,"text":"Lake Ecosystems Group, Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK.","active":true,"usgs":false}],"preferred":false,"id":704250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santoso, Arianto","contributorId":194468,"corporation":false,"usgs":false,"family":"Santoso","given":"Arianto","email":"","affiliations":[],"preferred":false,"id":704251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corman, Jessica","contributorId":194469,"corporation":false,"usgs":false,"family":"Corman","given":"Jessica","affiliations":[],"preferred":false,"id":704252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaimes, Aline","contributorId":194470,"corporation":false,"usgs":false,"family":"Jaimes","given":"Aline","email":"","affiliations":[],"preferred":false,"id":704253,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nodine, Emily","contributorId":194471,"corporation":false,"usgs":false,"family":"Nodine","given":"Emily","email":"","affiliations":[],"preferred":false,"id":704254,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patil, Vijay P. 0000-0002-9357-194X vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":203676,"corporation":false,"usgs":true,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":704255,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":704256,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brentrup, Jennifer A.","contributorId":194457,"corporation":false,"usgs":false,"family":"Brentrup","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704257,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hetherington, Amy","contributorId":150325,"corporation":false,"usgs":false,"family":"Hetherington","given":"Amy","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":704258,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":704259,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":704260,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Winter, Kirsten","contributorId":194473,"corporation":false,"usgs":false,"family":"Winter","given":"Kirsten","email":"","affiliations":[],"preferred":false,"id":704261,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hanson, Paul","contributorId":194474,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","affiliations":[],"preferred":false,"id":704262,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Read, Emily 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":190110,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":704263,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":704264,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Weathers, Kathleen","contributorId":191961,"corporation":false,"usgs":false,"family":"Weathers","given":"Kathleen","affiliations":[{"id":7188,"text":"Cary Institute of Ecosystem Studies, Millbrook, NY, USA","active":true,"usgs":false}],"preferred":false,"id":704265,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70178358,"text":"70178358 - 2016 - The 2016 groundwater flow model for Dane County, Wisconsin","interactions":[],"lastModifiedDate":"2017-01-03T14:13:59","indexId":"70178358","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":242,"text":"Bulletin","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"110","title":"The 2016 groundwater flow model for Dane County, Wisconsin","docAbstract":"A new groundwater flow model for Dane County, Wisconsin, replaces an earlier model developed in the 1990s by the Wisconsin Geological and Natural History Survey (WGNHS) and the U.S. Geological Survey (USGS). This modeling study was conducted cooperatively by the WGNHS and the USGS with funding from the Capital Area Regional Planning Commission (CARPC). Although the overall conceptual model of the groundwater system remains largely unchanged, the incorporation of newly acquired high-quality datasets, recent research findings, and improved modeling and calibration techniques have led to the development of a more detailed and sophisticated model representation of the groundwater system. The new model is three-dimensional and transient, and conceptualizes the county’s hydrogeology as a 12-layer system including all major unlithified and bedrock hydrostratigraphic units and two high-conductivity horizontal fracture zones.
Beginning from the surface down, the model represents the unlithified deposits as two distinct model layers (1 and 2). A single layer (3) simulates the Ordovician sandstone and dolomite of the Sinnipee, Ancell, and Prairie du Chien Groups. Sandstone of the Jordan Formation (layer 4) and silty dolostone of the St. Lawrence Formation (layer 5) each comprise separate model layers. The underlying glauconitic sandstone of the Tunnel City Group makes up three distinct layers: an upper aquifer (layer 6), a fracture feature (layer 7), and a lower aquifer (layer 8). The fracture layer represents a network of horizontal bedding-plane fractures that serve as a preferential pathway for groundwater flow. The model simulates the sandstone of the Wonewoc Formation as an upper aquifer (layer 9) with a bedding-plane fracture feature (layer 10) at its base. The Eau Claire aquitard (layer 11) includes shale beds within the upper portion of the Eau Claire Formation. This layer, along with overlying bedrock units, is mostly absent in the preglacially eroded valleys along the Yahara River valley and in northeastern Dane County. Layer 12 represents the Mount Simon sandstone as the lowermost model layer. It directly overlies the Precambrian crystalline basement rock, whose top surface forms the lower boundary of the model.
The model uses the USGS MODFLOW-NWT finite-difference code, a standalone version of MODFLOW-2005 that incorporates the Newton (NWT) solver. MODFLOW-NWT improves the handling of unconfined conditions by smoothing the transition from wet to dry cells. The model explicitly simulates groundwater–surface-water interaction with streamflow routing and lake-level fluctuation. Model input included published and unpublished hydrogeologic data from recent estimates of aquifer hydraulic conductivities. A spatial groundwater recharge distribution was obtained from a recent GIS-based, soil-water-balance model for Dane County. Groundwater withdrawals from pumping were simulated for 572 wells across the entire model domain, which includes Dane County and portions of seven neighboring counties—Columbia, Dodge, Green, Iowa, Jefferson, Lafayette, and Rock. These wells withdrew an average of 60 million gallons per day (mgd) over the 5-year period from 2006 through 2010. Within Dane County, 385 wells were simulated with an average withdrawal rate of 52 mgd.
Model calibration used the parameter estimation code PEST, and calibration targets included heads, stream and spring flows, lake levels, and borehole flows. Steady-state calibration focused on the period 2006 through 2010; the transient calibration focused on the 7-week drought period from late May through July 2012.
This model represents a significant step forward from previous work because of its finer grid resolution, improved hydrostratigraphic discretization, transient capabilities, and more sophisticated representation of surface-water features and multi-aquifer wells.
Potential applications of the model include evaluation of potential sites for and impacts of new high-capacity wells, development of wellhead protection plans, evaluating the effects of changing land use and climate on groundwater, and quantifying the relationships between groundwater and surface water.
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The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.
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2016 - Assessment of trace element accumulation by earthworms in an orchard soil remediation study using soil amendments","interactions":[],"lastModifiedDate":"2018-08-09T12:21:31","indexId":"70176062","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of trace element accumulation by earthworms in an orchard soil remediation study using soil amendments","docAbstract":"This study assessed potential bioaccumulation of various trace elements in grasses and earthworms as a consequence of soil incorporation of organic amendments for in situ remediation of an orchard field soil contaminated with organochlorine and Pb pesticide residues. In this experiment, four organic amendments of differing total organic carbon content and quality (two types of composted manure, composted biosolids, and biochar) were added to a contaminated orchard field soil, planted with two types of grasses, and tested for their ability to reduce bioaccumulation of organochlorine pesticides and metals in earthworms. The experiment was carried out in 4-L soil microcosms in a controlled environment for 90 days. After 45 days of orchardgrass or perennial ryegrass growth, Lumbricus terrestris L. were introduced to the microcosms and exposed to the experimental soils for 45 days before the experiment was ended. Total trace element concentrations in the added organic amendments were below recommended safe levels and their phytoavailablity and earthworm availability remained low during a 90-day bioremediation study. At the end of the experiment, total tissue concentrations of Cu, Cd, Mn, Pb, and Zn in earthworms and grasses were below recommended safe levels. Total concentrations of Pb in test soil were similar to maximum background levels of Pb recorded in soils in the Eastern USA (100 mg kg−1 d.w.) because of previous application of orchard pesticides. Addition of aged dairy manure compost and presence of grasses was effective in reducing the accumulation of soil-derived Pb in earthworms, thus reducing the risk of soil Pb entry into wildlife food chains.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s11270-016-3055-0","issn":"1573-2932","usgsCitation":"Centofantia, T., Chaney, R.L., Beyer, W.N., McConnell, L.L., Davis, A.P., and Jackson, D., 2016, Assessment of trace element accumulation by earthworms in an orchard soil remediation study using soil amendments: Water, Air, & Soil Pollution, v. 227, no. 9, 350; 14 p., https://doi.org/10.1007/s11270-016-3055-0.","productDescription":"350; 14 p.","ipdsId":"IP-073952","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":332598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","city":"Beltsville","otherGeospatial":"Beltsville Agricultural Research Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.92626953125,\n 38.9871677013526\n ],\n [\n -76.92626953125,\n 39.06184913429154\n ],\n [\n -76.82876586914061,\n 39.06184913429154\n ],\n [\n -76.82876586914061,\n 38.9871677013526\n ],\n [\n -76.92626953125,\n 38.9871677013526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"227","issue":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-31","publicationStatus":"PW","scienceBaseUri":"5864dd4de4b0cd2dabe7c1cb","contributors":{"authors":[{"text":"Centofantia, Tiziana","contributorId":150859,"corporation":false,"usgs":false,"family":"Centofantia","given":"Tiziana","email":"","affiliations":[{"id":18121,"text":"Department of Civil and Environmental Engineering, University of Maryland College","active":true,"usgs":false}],"preferred":false,"id":647028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chaney, Rufus L.","contributorId":35455,"corporation":false,"usgs":true,"family":"Chaney","given":"Rufus","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":647029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beyer, W. 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These islands are known for flora and fauna that occur nowhere else, but also for invasive species and other factors which have resulted in the disproportionate extinction of native species. The control of invasive mammals is the single most expensive natural resource management activity essential for restoring ecological integrity to parks in the Hawaiian Islands, American Samoa, and the islands of Guam and Saipan. Science-based applications supporting management efforts have been shaped by longstanding collaborative federal research programs over the past four decades. Consequently, feral goats (Capra hircus) have been removed from >690 km2 in National Parks, and feral pigs (Sus scrofa) have been removed from >367 km2 of federal lands of Hawai‘i, bringing about the gradual recovery of forest ecosystems. The exclusion of other non-native ungulates and invasive mammals is now being undertaken with more sophisticated control techniques and fences. New fence designs are now capable of excluding feral cats (Felis catus) from large areas to protect endangered native waterfowl and nesting seabirds. Rodenticides which have been tested and registered for hand and aerial broadcast in Hawai‘i have been used to eradicate rats from small offshore islands to protect nesting seabirds and are now being applied to montane environments of larger islands to protect forest birds. Forward-looking infrared radar (FLIR) is also being applied to locate wild ungulates which were more recently introduced to some islands. All invasive mammals have been eradicated from some remote small islands, and it may soon be possible to manage areas on larger islands to be free of invasive mammals at least during seasonally important periods for native species.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th Wildlife Damage Management Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"16th Wildlife Damage Management Conference","conferenceDate":"March 1-4, 2015","conferenceLocation":"Gatlinburg, TN","language":"English","publisher":"Auburn University","usgsCitation":"Hess, S.C., Hu, D., Loh, R., and Banko, P.C., 2016, Federal collaboration in science for invasive mammal management in U.S. National Parks and Wildlife Refuges of the Pacific Islands, in Proceedings of the 16th Wildlife Damage Management Conference, Gatlinburg, TN, March 1-4, 2015, p. 5-18.","productDescription":"14 p.","startPage":"5","endPage":"18","ipdsId":"IP-079373","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":339972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f877b8e4b0b7ea54521c14","contributors":{"editors":[{"text":"Conner, L.M.","contributorId":75254,"corporation":false,"usgs":true,"family":"Conner","given":"L.M.","email":"","affiliations":[],"preferred":false,"id":692170,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Smith, M. D.","contributorId":25724,"corporation":false,"usgs":false,"family":"Smith","given":"M.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":692171,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Hess, Steven C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":3156,"corporation":false,"usgs":true,"family":"Hess","given":"Steven","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":692166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, Darcy","contributorId":91734,"corporation":false,"usgs":true,"family":"Hu","given":"Darcy","email":"","affiliations":[],"preferred":false,"id":692167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loh, Rhonda","contributorId":191174,"corporation":false,"usgs":false,"family":"Loh","given":"Rhonda","email":"","affiliations":[],"preferred":false,"id":692168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":692169,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187744,"text":"70187744 - 2016 - Environmental extremes and biotic interactions facilitate depredation of endangered California Ridgway’s rail in a San Francisco Bay tidal marsh","interactions":[],"lastModifiedDate":"2017-05-16T15:44:08","indexId":"70187744","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1153,"text":"California Fish and Game","active":true,"publicationSubtype":{"id":10}},"title":"Environmental extremes and biotic interactions facilitate depredation of endangered California Ridgway’s rail in a San Francisco Bay tidal marsh","docAbstract":"On 23 December 2015 while performing a high tide population survey for endangered Ridgway’s rails (Rallus obsoletus obsoletus; formerly known as the California clapper rail) and other rail species at Arrowhead Marsh, Martin Luther King Jr. Regional Shoreline, Oakland, California, the authors observed a series of species interactions resulting in the predation of a Ridgway’s rail by an adult female peregrine falcon (Falco peregrinus). High tide surveys are performed during the highest tides of the year when tidal marsh vegetation at Arrowhead Marsh becomes inundated, concentrating the tidal marsh obligate species into the limited area of emergent vegetation remaining as refuge cover. Annual mean tide level (elevation referenced relative to mean lower low water) at Arrowhead Marsh is 1.10 m, mean higher high water is 2.04 m (NOAA National Ocean Service 2014) and the average elevation of the marsh surface is 1.60 m (Overton et al. 2014). Tidal conditions on the day of the survey were predicted to be 2.42 m. Observed tides at the nearby Alameda Island tide gauge were 8 cm higher than predicted due to a regional low-pressure system and warmer than average sea surface temperatures (NOAA National Ocean Service 2014). The approximately 80 cm deep inundation of the marsh plain was sufficient to completely submerge tidal marsh vegetation and effectively remove 90% of refugia habitats.
","language":"English","publisher":"California Department of Fish and Wildlife","usgsCitation":"Overton, C.T., Bobzien, S., and Grefsrud, M., 2016, Environmental extremes and biotic interactions facilitate depredation of endangered California Ridgway’s rail in a San Francisco Bay tidal marsh: California Fish and Game, v. 102, no. 4, p. 157-161.","productDescription":"5 p.","startPage":"157","endPage":"161","ipdsId":"IP-077798","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":341393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":341379,"type":{"id":11,"text":"Document"},"url":"https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=141860&inline"}],"volume":"102","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591c0fc8e4b0a7fdb43ddeee","contributors":{"authors":[{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":695401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bobzien, Steven","contributorId":167184,"corporation":false,"usgs":false,"family":"Bobzien","given":"Steven","email":"","affiliations":[{"id":24634,"text":"East Bay Regional Park District","active":true,"usgs":false}],"preferred":false,"id":695402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grefsrud, Marcia","contributorId":192076,"corporation":false,"usgs":false,"family":"Grefsrud","given":"Marcia","email":"","affiliations":[],"preferred":false,"id":695403,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194182,"text":"70194182 - 2016 - Origins of a national seismic system in the United States","interactions":[],"lastModifiedDate":"2019-07-10T14:10:19","indexId":"70194182","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Origins of a national seismic system in the United States","docAbstract":"This historical review traces the origins of the current national seismic system in the United States, a cooperative effort that unifies national, regional, and local‐scale seismic monitoring within the structure of the Advanced National Seismic System (ANSS). The review covers (1) the history and technological evolution of U.S. seismic networks leading up to the 1990s, (2) factors that made the 1960s and 1970s a watershed period for national attention to seismology, earthquake hazards, and seismic monitoring, (3) genesis of the vision of a national seismic system during 1980–1983, (4) obstacles and breakthroughs during 1984–1989, (5) consensus building and convergence during 1990–1992, and finally (6) the two‐step realization of a national system during 1993–2000. Particular importance is placed on developments during the period between 1980 and 1993 that culminated in the adoption of a charter for the Council of the National Seismic System (CNSS)—the foundation for the later ANSS. Central to this story is how many individuals worked together toward a common goal of a more rational and sustainable approach to national earthquake monitoring in the United States. The review ends with the emergence of ANSS during 1999 and 2000 and its statutory authorization by Congress in November 2000.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160039","usgsCitation":"Filson, J.R., and Arabasz, W.J., 2016, Origins of a national seismic system in the United States: Seismological Research Letters, v. 88, no. 1, p. 131-143, https://doi.org/10.1785/0220160039.","productDescription":"13 p.","startPage":"131","endPage":"143","ipdsId":"IP-070323","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":349025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-09","publicationStatus":"PW","scienceBaseUri":"5a60fc7de4b06e28e9c23f04","contributors":{"authors":[{"text":"Filson, John R. 0000-0001-8840-6301 jfilson@usgs.gov","orcid":"https://orcid.org/0000-0001-8840-6301","contributorId":5078,"corporation":false,"usgs":true,"family":"Filson","given":"John","email":"jfilson@usgs.gov","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":722560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arabasz, Walter J.","contributorId":200529,"corporation":false,"usgs":false,"family":"Arabasz","given":"Walter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":722561,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182075,"text":"70182075 - 2016 - Surveillance for Eurasian-origin and intercontinental reassortant highly pathogenic influenza A viruses in Alaska, spring and summer 2015","interactions":[],"lastModifiedDate":"2018-07-16T12:05:25","indexId":"70182075","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3697,"text":"Virology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Surveillance for Eurasian-origin and intercontinental reassortant highly pathogenic influenza A viruses in Alaska, spring and summer 2015","docAbstract":"Background: Eurasian-origin and intercontinental reassortant highly pathogenic (HP) influenza A viruses (IAVs) were first detected in North America in wild, captive, and domestic birds during November–December 2014. Detections of HP viruses in wild birds in the contiguous United States and southern Canadian provinces continued into winter and spring of 2015 raising concerns that migratory birds could potentially disperse viruses to more northerly breeding areas where they could be maintained to eventually seed future poultry outbreaks.
Results: We sampled 1,129 wild birds on the Yukon-Kuskokwim Delta, Alaska, one of the largest breeding areas for waterfowl in North America, during spring and summer of 2015 to test for Eurasian lineage and intercontinental reassortant HP H5 IAVs and potential progeny viruses. We did not detect HP IAVs in our sample collection from western Alaska; however, we isolated five low pathogenic (LP) viruses. Four isolates were of the H6N1 (n = 2), H6N2, and H9N2 combined subtypes whereas the fifth isolate was a mixed infection that included H3 and N7 gene segments. Genetic characterization of these five LP IAVs isolated from cackling (Branta hutchinsii; n = 2) and greater white-fronted geese (Anser albifrons; n = 3), revealed three viral gene segments sharing high nucleotide identity with HP H5 viruses recently detected in North America. Additionally, one of the five isolates was comprised of multiple Eurasian lineage gene segments.
Conclusions: Our results did not provide direct evidence for circulation of HP IAVs in the Yukon-Kuskokwim Delta region of Alaska during spring and summer of 2015. Prevalence and genetic characteristics of LP IAVs during the sampling period are concordant with previous findings of relatively low viral prevalence in geese during spring, non-detection of IAVs in geese during summer, and evidence for intercontinental exchange of viruses in western Alaska.
Widespread mercury (Hg) contamination of aquatic systems in the Sierra Nevada of California, U.S., is associated with historical use to enhance gold (Au) recovery by amalgamation. In areas affected by historical Au mining operations, including the western slope of the Sierra Nevada and downstream areas in northern California, such as San Francisco Bay and the Sacramento River–San Joaquin River Delta, microbial conversion of Hg to methylmercury (MeHg) leads to bioaccumulation of MeHg in food webs, and increased risks to humans and wildlife. This study focused on developing a predictive model for THg in stream fish tissue based on geospatial data, including land use/land cover data, and the distribution of legacy Au mines. Data on total mercury (THg) and MeHg concentrations in fish tissue and streambed sediment collected during 1980–2012 from stream sites in the Sierra Nevada, California were combined with geospatial data to estimate fish THg concentrations across the landscape. THg concentrations of five fish species (Brown Trout, Rainbow Trout, Sacramento Pikeminnow, Sacramento Sucker, and Smallmouth Bass) within stream sections were predicted using multi-model inference based on Akaike Information Criteria, using geospatial data for mining history and landscape characteristics as well as fish species and length (r2 = 0.61, p < 0.001). Including THg concentrations in streambed sediment did not improve the model's fit, however including MeHg concentrations in streambed sediment, organic content (loss on ignition), and sediment grain size resulted in an improved fit (r2 = 0.63, p < 0.001). These models can be used to estimate THg concentrations in stream fish based on landscape variables in the Sierra Nevada in areas where direct measurements of THg concentration in fish are unavailable.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.05.088","usgsCitation":"Alpers, C.N., Yee, J.L., Ackerman, J., Orlando, J.L., Slotton, D., and Marvin-DiPasquale, M.C., 2016, Prediction of fish and sediment mercury in streams using landscape variables and historical mining: Science of the Total Environment, v. 571, p. 364-379, https://doi.org/10.1016/j.scitotenv.2016.05.088.","productDescription":"16 p.","startPage":"364","endPage":"379","ipdsId":"IP-071053","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470382,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.05.088","text":"Publisher Index Page"},{"id":332083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"571","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585116bbe4b08138bf1abd50","contributors":{"authors":[{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":655815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":655816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orlando, James L. 0000-0002-0099-7221 jorlando@usgs.gov","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":1368,"corporation":false,"usgs":true,"family":"Orlando","given":"James","email":"jorlando@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":655817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Slotton, Darrell G.","contributorId":103361,"corporation":false,"usgs":true,"family":"Slotton","given":"Darrell G.","affiliations":[],"preferred":false,"id":655818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":655819,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179636,"text":"70179636 - 2016 - mizuRoute version 1: A river network routing tool for a continental domain water resources applications","interactions":[],"lastModifiedDate":"2017-01-09T11:33:05","indexId":"70179636","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"mizuRoute version 1: A river network routing tool for a continental domain water resources applications","docAbstract":"This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-9-2223-2016","usgsCitation":"Mizukami, N., Clark, M.P., Sampson, K., Nijssen, B., Mao, Y., McMillan, H., Viger, R.J., Markstrom, S.L., Hay, L.E., Woods, R., Arnold, J.R., and Brekke, L.D., 2016, mizuRoute version 1: A river network routing tool for a continental domain water resources applications: Geoscientific Model Development, v. 9, p. 2223-2238, https://doi.org/10.5194/gmd-9-2223-2016.","productDescription":"16 p.","startPage":"2223","endPage":"2238","ipdsId":"IP-075055","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-9-2223-2016","text":"Publisher Index Page"},{"id":332987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-23","publicationStatus":"PW","scienceBaseUri":"5874b0ade4b0a829a320bb67","contributors":{"authors":[{"text":"Mizukami, Naoki","contributorId":178120,"corporation":false,"usgs":false,"family":"Mizukami","given":"Naoki","email":"","affiliations":[],"preferred":false,"id":657982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Martyn P.","contributorId":178121,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":657983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sampson, Kevin","contributorId":178122,"corporation":false,"usgs":false,"family":"Sampson","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":657984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nijssen, Bart","contributorId":178123,"corporation":false,"usgs":false,"family":"Nijssen","given":"Bart","email":"","affiliations":[],"preferred":false,"id":657985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mao, Yixin","contributorId":139783,"corporation":false,"usgs":false,"family":"Mao","given":"Yixin","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":657986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMillan, Hilary","contributorId":176321,"corporation":false,"usgs":false,"family":"McMillan","given":"Hilary","email":"","affiliations":[],"preferred":false,"id":657987,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":657988,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":657989,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":657981,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Woods, Ross","contributorId":178124,"corporation":false,"usgs":false,"family":"Woods","given":"Ross","affiliations":[],"preferred":false,"id":657990,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Arnold, Jeffrey R.","contributorId":178125,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":657991,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brekke, Levi D.","contributorId":178126,"corporation":false,"usgs":false,"family":"Brekke","given":"Levi","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":657992,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70179765,"text":"70179765 - 2016 - Using continuous underway isotope measurements to map water residence time in hydrodynamically complex tidal environments","interactions":[],"lastModifiedDate":"2017-01-17T14:23:10","indexId":"70179765","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Using continuous underway isotope measurements to map water residence time in hydrodynamically complex tidal environments","docAbstract":"Stable isotopes present in water (δ2H, δ18O) have been used extensively to evaluate hydrological processes on the basis of parameters such as evaporation, precipitation, mixing, and residence time. In estuarine aquatic habitats, residence time (τ) is a major driver of biogeochemical processes, affecting trophic subsidies and conditions in fish-spawning habitats. But τ is highly variable in estuaries, owing to constant changes in river inflows, tides, wind, and water height, all of which combine to affect τ in unpredictable ways. It recently became feasible to measure δ2H and δ18O continuously, at a high sampling frequency (1 Hz), using diffusion sample introduction into a cavity ring-down spectrometer. To better understand the relationship of τ to biogeochemical processes in a dynamic estuarine system, we continuously measured δ2H and δ18O, nitrate and water quality parameters, on board a small, high-speed boat (5 to >10 m s–1) fitted with a hull-mounted underwater intake. We then calculated τ as is classically done using the isotopic signals of evaporation. The result was high-resolution (∼10 m) maps of residence time, nitrate, and other parameters that showed strong spatial gradients corresponding to geomorphic attributes of the different channels in the area. The mean measured value of τ was 30.5 d, with a range of 0–50 d. We used the measured spatial gradients in both τ and nitrate to calculate whole-ecosystem uptake rates, and the values ranged from 0.006 to 0.039 d–1. The capability to measure residence time over single tidal cycles in estuaries will be useful for evaluating and further understanding drivers of phytoplankton abundance, resolving differences attributable to mixing and water sources, explicitly calculating biogeochemical rates, and exploring the complex linkages among time-dependent biogeochemical processes in hydrodynamically complex environments such as estuaries.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.6b05745","usgsCitation":"Downing, B.D., Bergamaschi, B.A., Kendall, C., Kraus, T.E., Dennis, K.J., Carter, J.A., and von Dessonneck, T., 2016, Using continuous underway isotope measurements to map water residence time in hydrodynamically complex tidal environments: Environmental Science & Technology, v. 50, no. 24, p. 13387-13396, https://doi.org/10.1021/acs.est.6b05745.","productDescription":"10 p.","startPage":"13387","endPage":"13396","ipdsId":"IP-072168","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":470380,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.6b05745","text":"Publisher Index Page"},{"id":438500,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H70D0N","text":"USGS data release","linkHelpText":"Continuous underway water quality and water isotope measurements in a hydrodynamically complex tidal environment"},{"id":333260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento−San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.69898986816406,\n 38.2225380989223\n ],\n [\n -121.69898986816406,\n 38.37019391098433\n ],\n [\n -121.63650512695312,\n 38.37019391098433\n ],\n [\n -121.63650512695312,\n 38.2225380989223\n ],\n [\n -121.69898986816406,\n 38.2225380989223\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"24","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-06","publicationStatus":"PW","scienceBaseUri":"587f3bf9e4b0d96de256453f","contributors":{"authors":[{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":658597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, Carol 0000-0002-0247-3405 ckendall@usgs.gov","orcid":"https://orcid.org/0000-0002-0247-3405","contributorId":1462,"corporation":false,"usgs":true,"family":"Kendall","given":"Carol","email":"ckendall@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":658598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraus, Tamara E. 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Water storage is a key uncertainty in the boreal water budget, with tree water storage often ignored. The goal of this study is to quantify tree water content during the snowmelt and growing season periods for Alaskan and western Canadian boreal forests. Deciduous trees reached saturation between snowmelt and leaf-out, taking up 21–25% of the available snowmelt water, while coniferous trees removed <1%. We found that deciduous trees removed 17.8–20.9 billion m3 of snowmelt water, which is equivalent to 8.7–10.2% of the Yukon River’s annual discharge. Deciduous trees transpired 2–12% (0.4–2.2 billion m3) of the absorbed snowmelt water immediately after leaf-out, increasing favorable conditions for atmospheric convection, and an additional 10–30% (2.0–5.2 billion m3) between leaf-out and mid-summer. By 2100, boreal deciduous tree area is expected to increase by 1–15%, potentially resulting in an additional 0.3–3 billion m3 of snowmelt water removed from the soil per year. This study is the first to show that deciduous tree water uptake of snowmelt water represents a large but overlooked aspect of the water balance in boreal watersheds.
","language":"English","publisher":"Nature","doi":"10.1038/srep29504","usgsCitation":"Young, J., Bolton, W.R., Bhatt, U., Cristobal, J., and Thoman, R., 2016, Deciduous trees are a large and overlooked sink for snowmelt water in the boreal forest: Scientific Reports, v. 6, p. 1-10, https://doi.org/10.1038/srep29504.","productDescription":"Article 29504; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-070469","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":470389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep29504","text":"Publisher Index Page"},{"id":336967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"58bfd4f1e4b014cc3a3ba490","contributors":{"authors":[{"text":"Young, Jessica jmyoung@usgs.gov","contributorId":187609,"corporation":false,"usgs":true,"family":"Young","given":"Jessica","email":"jmyoung@usgs.gov","affiliations":[],"preferred":true,"id":681043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bolton, W. Robert","contributorId":187610,"corporation":false,"usgs":false,"family":"Bolton","given":"W.","email":"","middleInitial":"Robert","affiliations":[],"preferred":false,"id":681044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bhatt, Uma","contributorId":187611,"corporation":false,"usgs":false,"family":"Bhatt","given":"Uma","affiliations":[],"preferred":false,"id":681045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cristobal, Jordi","contributorId":187612,"corporation":false,"usgs":false,"family":"Cristobal","given":"Jordi","email":"","affiliations":[],"preferred":false,"id":681046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thoman, Richard","contributorId":187613,"corporation":false,"usgs":false,"family":"Thoman","given":"Richard","affiliations":[],"preferred":false,"id":681047,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179640,"text":"70179640 - 2016 - Hydrology of prairie wetlands: Understanding the integrated surface-water and groundwater processes","interactions":[],"lastModifiedDate":"2017-01-09T11:08:12","indexId":"70179640","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Hydrology of prairie wetlands: Understanding the integrated surface-water and groundwater processes","docAbstract":"Wetland managers and policy makers need to make decisions based on a sound scientific understanding of hydrological and ecological functions of wetlands. This article presents an overview of the hydrology of prairie wetlands intended for managers, policy makers, and researchers new to this field (e.g., graduate students), and a quantitative conceptual framework for understanding the hydrological functions of prairie wetlands and their responses to changes in climate and land use. The existence of prairie wetlands in the semi-arid environment of the Prairie-Pothole Region (PPR) depends on the lateral inputs of runoff water from their catchments because mean annual potential evaporation exceeds precipitation in the PPR. Therefore, it is critically important to consider wetlands and catchments as highly integrated hydrological units. The water balance of individual wetlands is strongly influenced by runoff from the catchment and the exchange of groundwater between the central pond and its moist margin. Land-use practices in the catchment have a sensitive effect on runoff and hence the water balance. Surface and subsurface storage and connectivity among individual wetlands controls the diversity of pond permanence within a wetland complex, resulting in a variety of eco-hydrological functionalities necessary for maintaining the integrity of prairie-wetland ecosystems.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0797-9","usgsCitation":"Hayashi, M., van der Kamp, G., and Rosenberry, D.O., 2016, Hydrology of prairie wetlands: Understanding the integrated surface-water and groundwater processes: Wetlands, v. 36, no. s2, p. 237-254, https://doi.org/10.1007/s13157-016-0797-9.","productDescription":"18 p.","startPage":"237","endPage":"254","ipdsId":"IP-076830","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":332982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"s2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-14","publicationStatus":"PW","scienceBaseUri":"5874b0ade4b0a829a320bb63","contributors":{"authors":[{"text":"Hayashi, Masaki","contributorId":173855,"corporation":false,"usgs":false,"family":"Hayashi","given":"Masaki","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":658013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van der Kamp, Garth","contributorId":178136,"corporation":false,"usgs":false,"family":"van der Kamp","given":"Garth","email":"","affiliations":[],"preferred":false,"id":658014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":658012,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}